스마트팜형 시설 딸기에 예찰 없이 작물 정식 초기에 천적을 먼저 적용하는 생태공학적 Natural Enemy in First (NEF) 기법이 총채벌레류 와 진딧물류의 밀도에 미치는 영향을 확인하였다. 대조구는 약제를 처리하여 비교하였다. NEF 처리구에서 총채벌레류와 진딧물류의 천적과 서식 처로 참멋애꽃노린재와 Portulaca sp.를 적용하여 작기 종료시점까지 해충의 밀도를 대조구와 유사하게 효과적으로 관리할 수 있었다.

Tuned mass damper (TMD) is widely used to reduce dynamic responses of structures subjected to earthquake loads. A smart tuned mass damper (STMD) was proposed to increase control performance of a traditional passive TMD. A lot of research was conducted to investigate the control performance of a STMD based on analytical method. Experimental study of evaluation of control performance of a STMD was not widely conducted to date. Therefore, seismic response reduction capacity of a STMD was experimentally investigated in this study. For this purpose, a STMD was manufactured using an MR (magnetorheological) damper. A simple structure presenting dynamic characteristics of spacial roof structure was made as a test structure. A STMD was made to control vertical responses of the test structure. Two artificial ground motions and a resonance harmonic load were selected as experimental seismic excitations. Shaking table test was conducted to evaluate control performance of a STMD. Control algorithms are one of main factors affect control performance of a STMD. In this study, a groundhook algorithm that is a traditional semi-active control algorithm was selected. And fuzzy logic controller (FLC) was used to control a STMD. The FLC was optimized by multi-objective genetic algorithm. The experimental results presented that the TMD can effectively reduce seismic responses of the example structures subjected to various excitations. It was also experimentally shown that the STMD can more effectively reduce seismic responses of the example structures conpared to the passive TMD.

Recently, machine learning is widely used to solve optimization problems in various engineering fields. In this study, machine learning is applied to development of a control algorithm for a smart control device for reduction of seismic responses. For this purpose, Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm. A single degree of freedom (SDOF) structure with a smart tuned mass damper (TMD) was used as an example structure. A smart TMD system was composed of MR (magnetorheological) damper instead of passive damper. Reward design of reinforcement learning mainly affects the control performance of the smart TMD. Various hyperparameters were investigated to optimize the control performance of DQN-based control algorithm. Usually, decrease of the time step for numerical simulation is desirable to increase the accuracy of simulation results. However, the numerical simulation results presented that decrease of the time step for reward calculation might decrease the control performance of DQN-based control algorithm. Therefore, a proper time step for reward calculation should be selected in a DQN training process.

A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

This study is about the control method of smart skin applying SPD(Suspended Particles Display). Smart skin is a self-developed composite window system for the purpose of reducing the cooling load and lighting load. The simulation by TRNSYS18 was modeled in detail based on an actual office located in Jeonju. The previously studied smart skin control method (case1) is a time-dependent control method, and a new control method (case2) was devised based on the data that consideration of daily insolation is important in an actual environment. As a result of simulation by case1, it was found that the amount of cooling energy and lighting energy saved was reduced by 15.1% and 39.2%, respectively, compared to the general model. As a result of the simulation by case2, it was found that the amount of cooling energy and lighting energy saved was reduced to 17.6% and 57.5%, respectively, compared to the general model. Therefore, the newly proposed control method considering the amount of insolation and time was found to be effective in reducing cooling energy and lighting energy.

In this study, a smart skin system that combines SPD (suspended particle display) and LGG (Lighting Guide Glass) and its optimal control method was developed for the purpose of simultaneously reducing the lighting load and cooling load in office buildings. And a demonstration site was built to test the results. The demonstration site was constructed as an experimental group with a smart skin system installed and a control group with a general window system installed. When the cooling energy consumption of the experimental group to which the smart skin system was applied was reduced by about 36.9% compared to the control group, the lighting energy was also reduced by 54.4%.

In this study, an algorithm for control of SPD(Suspended Particles Display) on Smart Skin was proposed. The office with SPD located in Jeonju, Jeollabuk-do was modeled and simulated using TRNSYS18. Through simulation, the energy and lighting consumption of building were analyzed The two kinds of control algorithm(SPD and dimming control method for cool energy and lighting energy saving(CASE 1) and improved control method(CASE 2)) were compared. For this research, Two models(with and without SPD and dimming control) were analyzed by comparing the cooling energy and the light energy consumption was reduced 15.1%, and the lightind energy consumption was reduced by 39.2% more than the model without SPD and dimming control. But, at the improved control method(CASE 2) the cooling energy consumption was reduced of more 2.5% and lighting energy consumptions was reduced of more 18.3% than CASE 1. When using SPD and dimming control, lighting energy consumptions showed more sensitive to solar radiation than cooling energy consumptions. As the improved control method(CASE 2) showed more advantageous saving tate than SPD and dimming control metrhod for cool energy and lighting energy saving(CASE 1), it was found that the improved control method (CASE 2) must be utilized in practice for SPD and dimming control.

A smart connective control system was invented recently for coupling control of adjacent buildings. Previous studies on this topic focused on development of control algorithm for the smart connective control system and design method of control device. Usually, a smart control devices are applied to building structures after structural design. However, because structural characteristics of building structure with control devices changes, a iterative design is required for optimal design. To defeat this problem, an integrated optimal design method for a smart connective control system and connected buildings was proposed. For this purpose, an artificial seismic load was generated for control performance evaluation of the smart coupling control system. 20-story and 12-story adjacent buildings were used as example structures and an MR (magnetorheological) damper was used as a smart control device to connect adjacent two buildings. NSGA-II was used for multi-objective integrated optimization of structure-smart control device. Numerical simulation results show the integrated optimal design method proposed in this study can provide various optimal designs for smart connective control system and connected buildings presenting good control performance.

In order to increase the production efficiency of the ship and shorten the production cycle, it is important to evaluate the accuracy of the ship components efficiently during the drying cycle. The accuracy control of the block is important for shortening the ship process, reducing the cost, and improving the accuracy of the ship. Some systems have been developed and used mainly in large shipyards, but in some cases, they are measured and managed using conventional measuring instruments such as tape measure and beam, optical instruments as optical equipment, In order to perform accuracy control, these tools and equipment as well as equipment for recording measurement data and paper drawings for measuring the measurement position are inevitably combined. The measured results are managed by the accuracy control system through manual input or recording device. In this case, the measurement result is influenced by the work environment and the skill level of the worker. Also, in the measurement result management side, there are a human error about the lack of the measurement result creation, the lack of the management sheet management, And costs are lost in terms of efficiency due to consumption. The purpose of this study is to improve the working environment in the existing accuracy management process by using the augmented reality technology to visualize the measurement information on the actual block and to obtain the measurement information And a smart management system based on augmented reality that can effectively manage the accuracy management data through interworking with measurement equipment. We confirmed the applicability of the proposed system to the accuracy control through the prototype implementation.

A connected control method for the adjacent buildings has been studied to reduce dynamic responses. In these studies, seismic loads were generally used as an excitation. Recently, multi-hazards loads including earthquake and strong wind loads are employed to investigate control performance of various control systems. Accordingly, strong wind load as well as earthquake load was adopted to evaluate control performance of adaptive smart coupling control system against multi-hazard. To this end, an artificial seismic load in the region of strong seismicity and an artificial wind load in the region of strong winds were generated for control performance evaluation of the coupling control system. Artificial seismic and wind excitations were made by SIMQKE and Kaimal spectrum based on ASCE 7-10. As example buildings, two 20-story and 12-story adjacent buildings were used. An MR (magnetorheological) damper was used as an adaptive smart control device to connect adjacent two buildings. In oder to present nonlinear dynamic behavior of MR damper, Bouc-Wen model was employed in this study. After parametric studies on MR damper capacity, optimal command voltages for MR damper on each seismic and wind loads were investigated. Based on numerical analyses, it was shown that the adaptive smart coupling control system proposed in this study can provide very good control performance for Multi-hazards.

A retractable-roof spatial structure is frequently used for a stadium and sports hall. A retractable-roof spatial structure allows natural lighting, ventilation, optimal conditions for grass growth with opened roof. It can also protects users against various weather conditions and give optimal circumstances for different activities. Dynamic characteristics of a retractable-roof spatial structure is changed based on opened or closed roof condition. A tuned mass damper (TMD) is widely used to reduce seismic responses of a structure. When a TMD is properly tuned, its control performance is excellent. Opened or closed roof condition causes dynamic characteristics variation of a retractable-roof spatial structure resulting in off-tuning. This dynamic characteristics variation was investigated. Control performance of a passive TMD and a smart TMD were evaluated under off-tuning condition.

An outrigger damper system has been proposed to reduce dynamic responses of tall buildings. In previous studies, an outrigger damper system was optimally designed to decrease a wind-induced or earthquake-induced dynamic response. When an outrigger damper system is optimally designed for wind excitation, its control performance for seismic excitation deteriorates. Therefore, a smart outrigger damper system is proposed in this study to make a control system that can simultaneously reduce both wind and seismic responses. A smart outrigger system is made up of MR (Magnetorheological) dampers. A fuzzy logic control algorithm (FLC) was used to generate command voltages sent for smart outrigger damper system and the FLC was optimized by genetic algorithm. This study shows that the smart outrigger system can provide good control performance for reduction of both wind and earthquake responses compared to the general outrigger system.

A novel vibration control method for vibration reduction of a spacial structure subjected to earthquake excitation was proposed in this study. Generally, spatial structures have various vibration modes involving high-order modes and their natural frequencies are closely spaced. Therefore, in order to control these modes, a spatially distributed MTMDs (Multiple TMDs) method is proposed previously. MR (Magnetorheological) damper were used to enhance the control performance of the MTMDs. Accordingly, MSTMDs (Multiple Smart TMDs) were proposed in this study. An arch structure was used as an example structure because it has primary characteristics of spatial structures and it is a comparatively simple structure. MSTMDs were applied to the example arch structure and the seismic control performance were evaluated based on the numerical simulation. Fuzzy logic control algorithm (FLC) was used to generate command voltages sent for MSTMSs and the FLC was optimized by genetic algorithm. Based on the analytical results, it has been shown that the MSTMDs effectively decreased the dynamic responses of the arch structure subjected to earthquake loads.

A shared tuned mass damper (STMD) was proposed in previous research for reduction of dynamic responses of the adjacent buildings subjected to earthquake loads. A single STMD can provide similar control performance in comparison with two traditional TMDs. In previous research, a passive damper was used to connect the STMD with adjacent buildings. In this study, a smart magnetorheological (MR) damper was used instead of a passive damper to compose an adaptive smart STMD (ASTMD). Control performance of the ASTMD was investigated by numerical analyses. For this purpose, two 8-story buildings were used as example structures. Multi-input multi-output (MIMO) fuzzy logic controller (FLC) was used to control the command voltages sent to two MR dampers. The MIMO FLC was optimized by a multi-objective genetic algorithm. Numerical analyses showed that the ASTMD can effectively control dynamic responses of adjacent buildings subjected to earthquake excitations in comparison with a passive STMD.

In this study, a smart isolation platform has been developed for control of microvibration of high-technology facilities, such as semi-conductor plants and TFT-LCD plants. Previously, microvibration control performance of a smart base isolation system has been investigated. This study compared microvibration control performance of a smart isolation platform with that of conventional base isolation and fixed base. For this purpose, train-induced ground acceleration is used for time history analysis. An MR damper was used to compose a smart isolation platform. A fuzzy logic controller was used as a control algorithm and it was optimized by a multi-objective genetic algorithm. Numerical analysis shows that a smart isolation platform can effectively control microvibration of a high-technology facility subjected to train-induced excitation compared with other models.